DNA Barcoding and Mini-DNA Barcoding Reveal Mislabeling of Salmonids in Different Distribution Channels in the Qingdao Area

HAN Cui, DONG Shuanglin, LI Li, *, GAO Qinfeng, and ZHOU Yangen

DNA Barcoding and Mini-DNA Barcoding Reveal Mislabeling of Salmonids in Different Distribution Channels in the Qingdao Area

HAN Cui1), 2), DONG Shuanglin1), 2), LI Li1), 2), *, GAO Qinfeng1), 2), and ZHOU Yangen1), 2)

1),,,266003,2),,266235,

There is an increasing demand for salmonid authentication due to theglobalization of the salmonid trade. DNA barcoding and mini-DNA barcoding are widely used for identifying fish species based on a fragment of the mitochondrial cytochrome c oxidase subunit I () sequence. In this study, rainbow trout (),steelhead trout (), and Atlantic salmon () collected from two salmonid aquaculture bases in China were authenticated by DNA barcoding (about 650bp) and mini-DNA barcoding (127bp)to evaluate the accuracy of the two methods in the identification of different salmonid species. The results revealed that both methods could effectively distinguishandwith 100% accuracy. However, the two methods failed to separate rainbow trout () and steelhead trout (), which are the same species but cultured in different water environments.Moreover, salmonid samples from three main distribution channels in the Qingdao area (traditional supermarkets, online supermarkets, and sushi bars) were identified by the two methods. Substitution ofwithwas discovered, and the 27.78% overall substitution rate of salmonids in the Qingdao area was higher than those in other regions reported in previous studies. In addition, the mislabeling rates of salmonids from traditional supermarkets, online supermarkets, and sushi bars were compared in this study. The mislabeling rate was significantly greater in sushi bars (50%) than in the other two channels (16.67%), suggesting that stronger monitoring and enforcement measures are necessary for the aquatic food catering industry.

salmonid; DNA barcoding; mini-DNA barcoding; species authentication; mislabeling rate

1 Introduction

The globalization of the food trade, especially that of fish and fishery products, has developed rapidly in recent decades. The management and tracing of the fishery sup- ply chain has subsequently become complex, and fishery market disorder driven by international trade has become a serious global problem (Wong and Hanner, 2008; Huang., 2014; Armani., 2015b; Jie., 2018; Pa- zartzi., 2019). Substituting high-value species with lower value ones or even endangered or prohibited spe- cies for financial gain has been frequently reported (Wong and Hanner, 2008; Hanner., 2011; Cline, 2012; Pa- zartzi., 2019). Inadvertent or deliberate mislabeling is common in the aquatic market due to the absence ofmorphological characteristics in processed products (fil-lets or cooked products), which has potential ramificationsfor public health and ecological and economic implications(Veneza., 2014; Addisu., 2015). Therefore, aqua- tic food authenticity is becoming increasingly important.

Rainbow trout (), steelhead trout () and Atlantic salmon () are the most economically important cold-water aquaculturesalmonidspecies in China and are gaining popularity due to their unique nutritional value (Bechtel and Oliveira, 2010; Sar- ma., 2013; Addisu., 2015; Liu., 2018)(Addisu & Takele, 2015){Addisu Demeke Teklemariam, 2015 #228;Liu, 2018 #288;Sarma, 2013 #289}. How- ever, the taste of aquatic animals differs across species (Ra- hman, 2014), and some consumers prefer Atlantic salmon over rainbow trout, while others may have a different pre- ference. Processed fish products (such as fillets) in markets, however, are very difficult to authenticate by species due to the lack of morphological characteristics (Hu., 2018),and salmonid products are commonly mislabeled (Rasmus- sen., 2010; Dudu., 2011; Xiong., 2017; Mu- nozcolmenero., 2019; Xiong., 2020). Moreover, with the increasing globalization of the salmonid industry, the salmonid supply chains are complex, and the distribu- tion channels of salmonid products are diversified (Zhang., 2017),which creates loopholes for substitution be- havior in salmonid markets. Therefore, it is necessary to create reliable analytical techniques to identify different salmonid species to protect consumer interests and to su- pervise the mislabeling of salmonid products in every link of the supply chain (Rasmussen., 2010; Dudu., 2011), especially in diversified distribution channels.

DNA barcoding can be used to accurately authenticate fish products and has been widely applied in species au- thentication (Carvalho., 2015; Neumann, 2015; Ar- mani., 2015a; Shen., 2016; Pardo., 2018; Chen., 2019). DNA barcoding for fish authentication is based on approximately 650-bp sequence fragments of the mitochondrial gene cytochrome c oxidase subunit I () (Hebert., 2003). Databases (Barcode of Life Data- bases or BOLD, http://www.boldsystems.org/) for the au- thentication fish or other seafood have been establishedand have been accepted by some regulatory agencies world-wide (Hanner., 2011; Chen., 2019). However, DNA barcoding has exhibited some weaknesses in the au- thentication of preserved or processed fish samples due to DNA degradation (Hajibabaei and McKenna, 2012; Bhatta- charjee and Ghosh, 2014; Armani., 2015a; Vivien., 2016; Dhar and Ghosh, 2017). In this regard, mini-DNA barcoding, which uses smaller fragments (100–200bp) ofwithin the full-length DNA barcoding region, has been developed and applied in the authentication of some pro- cessed fishes (Armani., 2015a; Shokralla., 2015; Janjua., 2016). Nevertheless, the mini-DNA barcod- ing technique presents lower accuracy in the discrimina- tion of some fish species. Meusnier. (2008) illustrated that DNA barcoding could achieve an identification ac- curacy rate of 97%, whereas the identification rate based on 100bp mini-DNA barcoding declined to 90%. Further- more, mini-DNA barcoding was applied to identifyspecies, and 45.7% and 41.4% sequences were found to be unambiguously identified at the species level com- pared with the BOLD and GenBank databases, respective-ly (Armani., 2015a). Therefore, the availability ofDNA barcoding and mini-DNA barcoding for species iden- tification should be evaluated before they are applied to salmonid species authentication.

In the present study, salmonids collected from two aqua-culture bases were identified by DNA barcoding and mini-DNA barcoding methods to estimate the validity of the twomethods. Moreover, salmonid samples were purchased from three main distribution channels in Qingdao area,includ- ing traditional supermarkets, online supermarkets, and su- shi bars.They were identified by the two methods to investigate the replacement rate of salmonid products in dif-ferent distribution channels in this area.

2 Materials and Methods

2.1 Sampling

Rainbow trout (=12) and steelhead trout (=12) were collected from the Wanzefeng Salmonid Aquaculture Basewhich is located in Rizhao,China).Atlantic salmonsam- ples (=12) were collected from the Oriental Sea Sal- monid Aquaculture Basethat is located in Yantai, China. Collected fish were anesthetized using MS-222 and dis- sected immediately; fillets were placed on dry ice and transported to the laboratory in the Ocean University of China, Qingdao, China. In addition, a total of 18 samples (fresh muscle fillet) labeled as Atlantic salmon were pur- chased from local supermarkets (=6), online supermar- kets (=6), and sushi bars (=6).They were placed on ice and transported to the laboratory. All samples were fixed with 96% ethanol and stored at −80℃ for analysis (Sar- miento-Camacho and Valdez-Moreno, 2018).

2.2 DNA Extraction

Total DNA was extracted from fish samples using Qia- gen DNeasy Blood & Tissue kits (Qiagen, Hilden, Ger- many) following the manufacturer’s instructions. Briefly, 10mg fish muscle tissue was mixed with 180μL of ATL buffer and 20μL of proteinase K and incubated at 56℃until completely dissolved. Then 200μL AL buffer and 200μL ethanol were added and mixed. The mixture was trans- ferred to the spin column and centrifuged for 1min at 8000 rmin−1. Next, the spin column was washed with buffer AW1 and AW2. Lastly, DNA extraction was recovered with AE buffer. The concentration of DNA was measured using a spectrophotometer(Nano-300, Hangzhou Allsheng Instru- ments Co., Ltd., Hangzhou, China).

2.3 PCR and DNA Sequencing

DNA barcoding (about 650bp) of thegene was used to authenticate 54 samples by PCR. PCR amplification of DNA fragments for DNA barcoding was carried out using a combination of the VF2_t1 and FR1d_t1 (Table 1) pri- mers with M13 tails described by Bosko. (2018) and Hu. (2018). The 25-μL PCR reaction mixtures con- tained 2.5μL of 10× Platinum Taq PCR Buffer, 1μL of 50 mmolL−1MgCl2, 0.5μL of 10mmolL−1dNTPs, 1μL of each forward and reverse primers working solutions, 0.2μL of Platinum Taq polymerase, 2μL of fish DNA, and 16.8μL of sterile water. Cycling conditions consisted of one cycle at 94℃ for 2min; 35 cycles at 94℃ for 30s, 52℃ for 40s, and 72℃ for 1min; with a final extension at 72℃ for 10min and held at 4℃.

Table 1 Primers for DNA barcode and mini-DNA barcode of salmonids

For mini-DNA barcoding, the primers UniMiniBar_F and UniMiniVar_R with M13 tails were used in PCR to am- plify the sequence of a 127bp mitochondrialDNA fragment as described by Bosko. (2018) and Hu. (2018). The PCR reaction mixtures were the same as in the DNA barcoding method. The cycling conditions con- sisted one cycle at 95℃ for 2min; 5 cycles at 95℃ for 1min, 46℃ for 1min, and 72℃ for 30s; 35 cycles at 95℃ for 1min, 53℃ for 1min, and 72℃ for 30s; with a final extension at 72℃ for 5min and held at 4℃.

The PCR-amplified products were examined using 1.5%agarose gel in 1× TAE buffer with GeneFinder (Super- Red/GelRed, Shanghai Li Rui Biological Technology Co., Ltd.). The successfully amplified PCR products were sent to Sangon Biotech (Shanghai) Co., Ltd. for sequencing.

2.4 Analysis of DNA Sequences

The sequences obtained were compared to the BOLD (http://www.boldsystems.org/) and GenBank (http://www. ncbi.nlm.nih.gov/genbank) databases. The fish samples could be identified to the species level with greater than 98% sequence similarity (Hu., 2018; Pardo.,2018). The phylogenetic analyses were performed by soft Mega 6.0, pairwise genetic distances among sequences were calculated, and Neighbor-joining tree analyses were carried out using the Kimura 2-parameter (K2P) distance model (Kimura, 1980). A bootstrap test with 2000 replica- tions was used to evaluate the reliability of the Neighbor- joining tree (Pardo., 2018).

3 Results and Discussion

3.1 Discriminating Salmonids by the DNA Barcoding Method

The sizes of the DNA barcoding sequences of rainbow trout, steelhead trout, and Atlantic salmon were 653bp, 653bp, and 652bp, respectively (Table 2). These sequences were submitted to GenBank under the accession number of MN245088-MN245123. The salmonid samples collect- ed from the two aquaculture bases were 100% correctly identified to the species level by the DNA barcoding me- thod. By matching thesequences with the sequences of reference species in the BOLD database or GenBank (National Center for Biotechnology Information, NCBI), the similarity reached 100% (Table 2). Successful identi- fication of salmonid species based on DNA barcoding had been previously reported (Willette., 2017; Hu., 2018, Pardo., 2018; Sarmiento-Camacho and Valdez- Moreno, 2018). The species(Atlantic salmon) and(rainbow trout or steelhead trout) wereidenti- fied using DNA barcoding in the present study. However, rainbow trout and steelhead trout could not be distinguish- ed by the method, as they were the same species with dif- ferent life history types (Docker and Heath, 2003).Rain- bow trout completed their entire life cycle in freshwater, and steelhead trout was an anadromous species, which re- mained in freshwater during the stages of adult spawning and egg and juvenile development and migrated to the ocean during the stage of juvenile growth into mature adult (Doc- ker and Heath, 2003; Alagona., 2012). Due to the dif- ferent culture environments, rainbow trout and steelhead trout might be identifiedthe stable isotope and multi- element analyses (Camin., 2017; Li., 2019; Han., 2020).

Table 2 Salmonid samples collected from two aquaculture bases detected by DNA barcoding (DB) and mini-DNA barcoding (MDB)

The pairwise intraspecies divergences of rainbow trout, steelhead trout, and Atlantic salmon were 0.001±0.001, 0.002±0.001, and 0.000±0.000, respectively. The genetic distance between rainbow trout and steelhead trout was 0.003±0.001. The genetic distances between Atlantic sal- mon and rainbow trout, and between Atlantic salmon and steelhead trout were 0.152±0.000 and 0.151±0.001, re- spectively. The interspecific genetic distance far exceeds the intraspecies genetic distance, indicating thatandcan be identified reliably using DNA bar- coding (Rasmussen., 2009). A phylogenetic analysis was performed via MEGA 6.0 software to demonstrate theintergeneric or interspecific phylogenetic relationship of sal- monid based on DNA barcoding sequences. In addition to the sequences ofandobtained in thisstudy, the sequences of seven other salmonid species, in- cluding(MG837977.1),(KJ55464 7.1),(KX145589.1),(KX145451.1),(EU524357.1),(EU522415.1), and(EEFF075-06) were downloadedfrom the GenBank and BOLD databases. The results show- ed thatandwere clustered together at the genus level,andbelonged to the same genus,andwere clus- tered together, andwas clustered as an individual branch (shown in Fig.1). At the species level, all thesamples collected from the Oriental Sea Salmonid Aquaculture Base and 13 samples bought from the three distribution channels were clustered together. All thesamples collected from the Wanzefeng Salmonid Aquaculture Base and five samples purchased from the three distribution channels were clustered together, as shownin Fig.1. This indicates that DNA barcoding is a reliable tool not onlyto differentiateand, but al- so to discriminate the two species from other salmonid spe- cies.

In addition, the DNA barcoding sequences of 18 samples purchased from the three distribution channels were also successfully amplified and authenticated. The length of the 18 sequences ranged from 624 to 653bp, with an average length of 650bp (Table 3). The results showed that 13 samples were identified as,and five samples were identified as. These sequences were submitted to GenBank under the accession number of MN245124-MN245141.

Fig.1 Neighbor-joining tree obtained through COI sequences of seven salmonid species. S. salar (MG837977.1), O. my- kiss (KX145451.1), O. keta (KX145589.1), Salvelinus alpinus (EU524357.1), S. malma (EU522415.1), S. obtusirostris (KJ554647.1), and Brachymystax lenok (EEFF075-06), download from NCBI or BOLD; DO1–DO6, DM1–DM6, and DS1–DS6, representing samples from online supermarkets, traditional supermarkets, and sushi bars, respectively; DSS, DST, and DRT represent Atlantic salmon (n=12), steelhead trout (n=12), and rainbow trout (n=12) collected from the two aquaculture bases.

Table 3 DNA barcoding detection of salmonid samples collected from three distribution channels in Qingdao area

3.2 Discriminating Salmonids by the Mini-DNA Barcoding Method

The mini-DNA barcoding sequences of the 36 salmo- nid samples obtained from the two salmonid aquaculture bases were compared with reference sequences in the Gen- Bank and BOLD databases. All the samples were correct- ly identified to the species level, and the similarity reach- ed 100% (Table 4). Previous studies had reported that the amplification rates of mini-DNA barcoding are consider- ably higher than those of DNA barcoding in ethanol-pre- served samples (Armani., 2015a; Pollack., 2018), but the accuracy of mini-DNA barcoding was lower than that of DNA barcoding for species authentication (Meus- nier., 2008; Yu and You, 2010; Armani., 2015a). In this study, the amplification rates and the accuracy of mini-DNA barcoding, which were both 100% for ethanol- preserved salmonid samples, were the same as those of the DNA barcoding method. Moreover, the genetic dis- tance betweenandbased on the mini- DNA barcoding sequence was found to be 0.131, which exceeded the intraspecies divergences of(0.000)and(0.000)calculated by the Kimura 2-para- meter model. This indicates that the mini-DNA barcoding method can also reliably discriminateand

Table 4 Mini-DNA barcoding (MDB) detection of salmonid samples collected from three distribution channels in Qingdao area

The mini-DNA barcoding sequences (127±0bp) of the samples collected from the three distribution channels wereamplified and identified successfully. Among them, 13 samples were identified as, and five samples were identified as(Table 4), which was the same as the results authenticated by DNA barcoding.

3.3 Mislabeling of Salmonid Samples

Salmonid substitutions were reported frequently in pre- vious studies. As Table 5 shows, 12% of Pacific salmonproducts were mislabeled asin the New York City, Austin, and San Francisco Bay area (Khaksar., 2015), and 11%in Washington State were misdescribed as,,(Cline, 2012). InEurope,was sold asand,was sold as, andwas sold asThe mis- labeling rate reached 10% (Pardo., 2018).andwere mislabeled asand, respectively, with an 8.75% mislabeling rate in Metro Vancouver, Canada (Hu., 2018). In this study, all the collected samples were labeled as, but five of the 18 samples were identified asby both the DNA barcoding and mini-DNA barcoding methods (Ta- bles 3 and 4). The average mislabeling rate of the salmo- nid products reached 27.78%. These results indicate that species substitution of salmonids is a global problem. Hu. (2018) suggested that the substitution ofandwithwas intentional be- cause theandwere more expen- sive than. There is a strong possibility that the mis- description ofasin the present study is a fraud, becauseis more popular and expensive thanin China (Zhang and Cai, 2006; Sun and Wang, 2010). Moreover, illegal substitution offor Atlantic salmon in China had been reported by Zhang and Cai (2006).

Table 5 Mislabeling rate of salmonids in authentication research in different areas

The mislabeling rates of salmonids detected in tradi- tional supermarkets, online supermarkets, and sushi bars ranged from 16.67% to 50% in this study (Fig.2). Regula- tions that combat the adulteration and mislabeling of foods have been implemented in many countries, such asAdmi- nistration for Market Regulation of China, 2019, http://gkml.samr.gov.cn/nsjg/bgt/201902/t20190217_289795.htmland U.S. Food and Drug Administration, 2013, https://www.regulations.gov/docket?D=FDA-013-N-21425.It isemphasized that aquatic products sold in markets must be labeled with their species name, production method, geographical origin, and production date,. (Aquatic Pro- duct Marking Management in Guangdong Province, 2011,http://zwgk.gd.gov.cn/006941338/201110/t20111019_287953.html; Ministry of Agriculture of the People’s Repub- lic of China, 2003, http://zwgk.gd.gov.cn/006941338/201110/t20111019_287953.html). Although the fish products sold in traditional supermarkets or online supermarketsarestrictly supervised, a lower mislabeling rate (16.67%) is still found. In China, the production of salmonids was only 44000t in 2017 (Bureau of Fisheries of Ministry of Agriculture and Rural Affairs of the People’s Republic of China., 2018), and 37800t of salmonid products were imported from several countries, such as the United States, Canada, Chile, Japan, and Norway (Zhao., 2015; Ad- ministration of Customs, P. R. China, 2018, http://43.248. 49.97/indexEn). The complexity of the aquatic food supply chain and differences between the commercial naming sys- tems in different countriescan lead to accidental substitu- tions in markets (Cline, 2012; Pardo., 2018).

Fig.2 The mislabeling rate of salmonids from three distribution channels in Qingdao, China.

The mislabeling rate of salmonids was the highest in su- shi bars and reached 50% (Fig.2). Previous studies have also revealed that the mislabeling rate of fish food in the catering industry was higher than that of supermarkets and retailers (Hanner., 2011; Cline, 2012; Benard-Capel- le., 2015; Khaksar., 2015; Hu., 2018; Par- do., 2018). About 33% of seafood samples collected from restaurants in Washington, D.C. were found to be potentially mislabeled (Stern., 2017). The mislabeling rate of seafood in takeaway food was found to be as high as 50% in Spain, Iceland, Finland, and Germany (Par- do., 2018). From 2012 to 2015, a 47% mislabeling rate of seafood in sushi restaurants in Los Angeles was reported (Willette., 2017). In summary, the higher mislabeling rate of seafood in the catering business was a global issue. This might be because there was a lack of re- gulations that require restaurants to provide detailed in- formation on food (such as species name, production me- thod, and geographical origin,.) to their customers (Par-do., 2018). Furthermore, as reported by Cawthorn. (2012), the complicated supply chain also contri- butes to the higher mislabeling rate in the catering busi- ness. In this study, the mislabeling rate in sushi bars was higher than that of supermarkets and online supermarkets, which suggested that a higher mislabeling rate occurred at the retail level rather than along the supply chain.

4 Conclusions

The DNA barcoding and mini-DNA barcoding techni- ques effectively discriminated different salmonid species,and. Both methods revealed the misla- beling behaviors of salmonid species that occur in the threemain distribution channels (traditional supermarkets, online supermarkets, and sushi bars) in the Qingdao area. Addi- tionally, a higher mislabeling rate was observed in sushi bars, indicating that stronger monitoring and enforcement are urgently needed in the aquatic food catering industry. There are still limitations with respect to sample size. Ad- ditional researches should include more samples. These two methods failed to separate rainbow trout and steel- head trout, which are the same species but live in differ- ent water environments. Other methods, including stable isotope analysis and trace element analysis, might be ex- plored in the future to identify rainbow trout and steel- head trout.

Acknowledgements

This work was supported by the National Key Research and Development Program of China (No. 2019YFD0901 000) and the Natural Science Foundation of Shandong Pro- vince, China (No. ZR2020MC194).

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